How Companies Are Already Using AI

Every few months it seems another study warns that a big slice of the workforce is about to lose their jobs because of artificial intelligence. Four years ago, an Oxford University study predicted 47% of jobs could be automated by 2033. Even the near-term outlook has been quite negative: A 2016 report by the Organization for Economic Cooperation and Development (OECD) said 9% of jobs in the 21 countries that make up its membership could be automated. And in January 2017, McKinsey’s research arm estimated AI-driven job losses at 5%. My own firm released a survey recently of 835 large companies (with an average revenue of $20 billion) that predicts a net job loss of between 4% and 7% in key business functions by the year 2020 due to AI.

Yet our research also found that, in the shorter term, these fears may be overblown. The companies we surveyed – in 13 manufacturing and service industries in North America, Europe, Asia-Pacific, and Latin America – are using AI much more frequently in computer-to-computer activities and much less often to automate human activities. “Machine-to-machine” transactions are the low-hanging fruit of AI, not people-displacement.

For example, our survey, which asked managers of 13 functions, from sales and marketing to procurement and finance, to indicate whether their departments were using AI in 63 core areas, found AI was used most frequently in detecting and fending off computer security intrusions in the IT department. This task was mentioned by 44% of our respondents. Yet even in this case, we doubt AI is automating the jobs of IT security people out of existence. In fact, we find it’s helping such often severely overloaded IT professionals deal with geometrically increasing hacking attempts. AI is making IT security professionals more valuable to their employers, not less.

In fact, although we saw examples of companies using AI in computer-to-computer transactions such as in recommendation engines that suggest what a customer should buy next or when conducting online securities trading and media buying, we saw that IT was one of the largest adopters of AI. And it wasn’t just to detect a hacker’s moves in the data center. IT was using AI to resolve employees’ tech support problems, automate the work of putting new systems or enhancements into production, and make sure employees used technology from approved vendors. Between 34% and 44% of global companies surveyed are using AI in in their IT departments in these four ways, monitoring huge volumes of machine-to-machine activities.

In stark contrast, very few of the companies we surveyed were using AI to eliminate jobs altogether. For example, only 2% are using artificial intelligence to monitor internal legal compliance, and only 3% to detect procurement fraud (e.g., bribes and kickbacks).

What about the automation of the production line? Whether assembling automobiles or insurance policies, only 7% of manufacturing and service companies are using AI to automate production activities. Similarly, only 8% are using AI to allocate budgets across the company. Just 6% are using AI in pricing.

Where to Find the Low-Hanging Fruit

So where should your company look to find such low-hanging fruit – applications of AI that won’t kill jobs yet could bestow big benefits? From our survey and best-practice research on companies that have already generated significant returns on their AI investments, we identified three patterns that separate the best from the rest when it comes to AI. All three are about using AI first to improve computer-to-computer (or machine-to-machine) activities before using it to eliminate jobs:

Put AI to work on activities that have an immediate impact on revenue and cost. When Joseph Sirosh joined in 2004, he began seeing the value of AI to reduce fraud, bad debt, and the number of customers who didn’t get their goods and suppliers who didn’t get their money. By the time he left Amazon in 2013, his group had grown from 35 to more than 1,000 people who used machine learning to make Amazon more operationally efficient and effective. Over the same time period, the company saw a 10-fold increase in revenue.

After joining Microsoft Corporation in 2013 as corporate vice president of the Data Group, Sirosh led the charge in using AI in the company’s database, big data, and machine learning offerings. AI wasn’t new at Microsoft. For example, the company had brought in a data scientist in 2008 to develop machine learning tools that would improve its search engine, Bing, in a market dominated by Google. Since then, AI has helped Bing more than double its share of the search engine market (to 20%); as of 2015, Bing generated more than a $1 billion in revenue every quarter. (That was the year Bing became a profitable business for Microsoft.) Microsoft’s use of AI now extends far beyond that, including to its Azure cloud computing service, which puts the company’s AI tools in the hands of Azure customers. (Disclosure: Microsoft is a TCS client.)

Look for opportunities in which AI could help you produce more products with the same number of people you have today. The AI experience of the 170-year-old news service Associated Press is a great case in point. AP found in 2013 a literally insatiable demand for quarterly earnings stories, but their staff of 65 business reporters could write only 6% of the earnings stories possible, given America’s 5,300 publicly held companies. The earnings news of many small companies thus went unreported on AP’s wire services (other than the automatically published tabular data). So that year, AP began working with an AI firm to train software to automatically write short earnings news stories. By 2015, AP’s AI system was writing 3,700 quarterly earnings stories – 12 times the number written by its business reporters. This is a machine-to-machine application of AI. The AI software is one machine; the other is the digital data feed that AP gets from a financial information provider (Zacks Investment Research). No AP business journalist lost a job. In fact, AI has freed up the staff to write more in-depth stories on business trends.

Start in the back office, not the front office. You might think companies will get the greatest returns on AI in business functions that touch customers every day (like marketing, sales, and service) or by embedding it in the products they sell to customers (e.g., the self-driving car, the self-cleaning barbeque grill, the self-replenishing refrigerator, etc.). Our research says otherwise. We asked survey participants to estimate their returns on AI in revenue and cost improvements, and then we compared the survey answers of the companies with the greatest improvements (call them “AI leaders”) to the answers of companies with the smallest improvements (“AI followers”). Some 51% of our AI leaders predicted that by 2020 AI will have its biggest internal impact on their back-office functions of IT and finance/accounting; only 34% of AI followers said the same thing. Conversely, 43% of AI followers said AI’s impact would be greatest in the front-office areas of marketing, sales, and services, yet only 26% of the AI leaders felt it would be there. We believe the leaders have the right idea: Focus your AI initiatives in the back-office, particularly where there are lots of computer-to-computer interactions in IT and finance/accounting.

Computers today are far better at managing other computers and, in general, inanimate objects or digital information than they are at managing human interactions. When companies use AI in this sphere, they don’t have to eliminate jobs. Yet the job-destroying applications of AI are what command the headlines: driverless cars and trucks, robotic restaurant order-takers and food preparers, and more.

Make no mistake: Automation and artificial intelligence will eliminate some jobs. Chatbots for customer service have proliferated; robots on the factory floor are real. But we believe companies would be wise to use AI first where their computers already interact. There’s plenty of low-hanging fruit there to keep them busy for years.

Source: Harvard Business Review-How Companies Are Already Using AI


Robots add real value when working with humans, not replacing them

In the popular media, we talk a lot about robots stealing jobs. But when we stop speculating and actually look at the real world of work, the impact of advanced robotics is far more nuanced and complicated. Issues of jobs and income inequality fade away, for example — there aren’t remotely enough robots to affect more than a handful of us in the practical sense.

Yet robots usually spell massive changes in the way that skilled work gets done: The work required to fly an F-16 in a combat zone is radically different from the work required to fly a Reaper, a semi-autonomous unmanned aerial vehicle, in that same zone.

Because they change the work so radically, robot-linked upheavals like this create a challenge: How do you train the next generation of professionals who will be working with robots?

My research into the increasing use of robotics in surgery offers a partial answer. But it has also uncovered trends that — if they continue — could have a major impact on surgical training and, as a result, the quality of future surgeries.

How do you train the next generation of professionals who will be working with robots?

As I have previously explained, robotic surgical systems allow for one (liable) senior surgeon to take near-complete control of the surgical act. This means trainees are involved less — far less — in performing surgical work, which spells trouble for the profession’s competence and legitimacy. Who wants to be operated on by a surgeon who has watched a lot of surgery, but done very little?

If we are at the cusp of a robotic era, I think there are some crucial lessons to be learned here for the world of skilled work in general.

A few points set the stage for these lessons. Many fiercely debate whether robotsare the equivalent of the canary in the coal mine or a red herring. Partially this is because we don’t agree on how to count them — are robots only mechanical devices guided by AI and fed data by sensors, or are they also things like software and process automation? The second of those groups is far, far bigger and has had far, far greater impact on jobs and the economy than the other.

Even if we count conservatively, there is reason to think that robots are about to have their “PC” moment. Robot development and investment are accelerating rapidly, and every year robots get dramatically more capable and less expensive — the Internet means that what one robot learns, many can learn instantly, for example.

If we’re about to see explosive growth in robotics, it is important to keep in mind that, in principle and in practice, robots add real value when they enhance human capability rather than replace humans. But what counts as enhancement or replacement changes when you look up close.

Paradoxically, for example, it looks like the Da Vinci Surgical System is reducing surgical capacity in practice. Traditionally, surgical residents learned the craft by assisting senior surgeons. This is partly due to a happy accident — surgeons needed more skilled arms and thus relied on residents for assistance. Residents could observe and, under the watchful eye and hands of senior surgeons, perform procedures or even take over. Senior surgeons typically retract tissue so the resident can cut or suture, for example.

Traditional surgical practice basically demanded that residents play every minute of the game, literally shoulder to shoulder with their mentor. That’s how surgical training has been done since the early 20th century.

Robotics upsets this dynamic.

In many Da Vinci procedures, residents find themselves on the edges of the playing field. When once they might get four hours of practice during a traditional operation, now they get 10-15 minutes during a Da Vinci procedure — if they get a chance to participate at all. It’s not that the robotics technology itself prevents residents from learning; the technology just makes it iPhone-easy for liability-saddled attending surgeons to assume complete control. The expert does the work, which is good for patients in the short run, but the profession itself is in a new kind of trouble.

So what’s the broader lesson here for the future of skilled work? Surgeons are one of the first professional groups to deeply integrate sophisticated robotics systems into their methods, and the result is that surgery itself is radically reconfigured. But as with others that have already crossed this threshold — like pilots — the rush to integrate the latest robotic system may obscure the need for wholesale revisions to training methods so that humans can learn to perform even better in collaboration with robotic systems.

Source: TechCrunch -Robots add real value when working with humans, not replacing them

With robots on the job, it won’t be IT as usual

With robotics making great strides and more companies welcoming robots into the workforce, IT managers need to start prepping for the changes coming their way.

“Robotics will probably touch every business over the next decade,” said Dan Olds, an analyst with OrionX. “I think we’re nearing a tipping point where more businesses will be adding robots and robotics to their operations. They’ll be doing everything from manufacturing, to delivering food to restaurant tables to cleaning chores and farming — and lots of stuff in between.”

While robots have been working on assembly lines and in giant warehouses for some time, they’ve become much more than giant hulking arms moving car doors and stacking boxes. With advances in technologies like artificial intelligence, computer vision and mobility, robots are taking on a host of new roles.

Late last summer, for instance, Lowe’s, the home improvement chain, announced plans to use customer-service robots in 11 stores in the San Francisco Bay area.

The Aloft hotel in Cupertino, Calif. is already using a robot butler to autonomously deliver snacks and small items to guests in their rooms.

And two delivery companies — Postmates and DoorDash — will use fleets of autonomous robots to bring orders directly to customers’ front doors. That means the robots will navigate through cities and on crowded sidewalks in Washington, D.C. and Silicon Valley.

“Over the last decade, robotics has started in industry after industry and that will continue to advance during the next 10 years,” said Jeff Kagan, an independent industry analyst. “Robotics will play a growing role in a number of businesses, from making cars to taking orders at McDonalds. Not only will more companies move into robotics, but robotics will do more as it gets more intelligent with A.I., the internet of things and the cloud.”

The trend means that CIOs and IT managers need to be prepared for an influx of robotics because introducing this technology isn’t as simple as firing up a fleet of humanoid robots and letting them loose in an office building. It’s going to take planning, new skills and thought about how robots will affect employees and require new infrastructure.

This is not going to be IT as usual.

“It’s very much a different mindset than traditional IT,” said Mike Gennert, a professor and director of the Robotics Engineering Program at Worcester Polytechnic Institute, in Worcester, Mass. “IT managers worry about how they manage information, how it’s used, how it’s stored and secured. But none of that has the ability to directly affect the physical world. Robots affect the real world. That brings issues IT managers have not had to confront.”

For instance, It’s bad enough if a company computer is hacked and it becomes part of a zombie botnet. But what if someone hijacks a company robot and makes it do things, harmful things, in the real world?

Here are a few things CIOs and IT managers should start to think about and prepare for:

It’s time to bring in new skills

Some large companies will need to consider hiring a CRO — a Chief Robotics Officer — to go along with their CIO and CTO. A CRO would be responsible for the company’s robotics strategy and how it’s integrated into the processes already in place.

“I think the need is already starting to show up,” said Gennert. “For somebody who’s in the fast food industry, you’ll want to know how robotics can be used in your plants [for] packaging foods and moving foods, and on-site in point-of-sales and logistically and cleaning up afterwards.”

However, hiring a CRO isn’t the only position IT managers will need to fill. They’ll also need to bring in IT workers with a background in robotics — people who understand computer vision, sensors, programming models and security models, and who can do more than basic repairs and maintain robotic code.

Companies will also need someone experienced in A.I., since it will be the smarts in autonomous machines.

“Applications of machine learning in robotics is on the rise,” said Taskin Padir, an associate professor of Electrical and Computer Engineering at Northeastern University, in Boston. “Each practical robot system will rely on some level of A.I. to become more adaptable to situations that cannot be foreseen by the robot’s programmers.”

And time to upgrade your own skills

While IT managers are looking to hire new employees, they should consider bolstering their own skill set so they understand enough about robotics to get them up and running.

“IT managers will need to become intimately familiar with their new robot charges,” said Olds. “I think the robot vendors will provide a lot of this training, which will make it easier for IT personnel to quickly come up to speed.”

However, Gennert thinks IT managers will need a deeper knowledge than they can get from a few tutorials.

“I think IT managers need enough of an understanding to get what the changes will be and what the new needs will be,” he said. “They’ll surely want to have more expertise on some bigger skills, like manipulation, perception and vision, navigation and locomotion. You’ll need more expertise than you’d get from a few webinars or short courses.”

One robot will not replace one human

While there are a variety of estimates and a lot of fears floating around about how many jobs robots might take in the next five to 10 years, it’s hard to calculate how bringing robots into the workplace will affect employee numbers.

“Don’t think of robots as a one-to-one replacement for employees,” said Olds. “Trying to ‘roboticize’ all the tasks an employee does is extremely difficult. I don’t think robots will be taking over everyone’s job.”

While some workers will be displaced, the majority will carry on as before. Some employees may have more mundane, physically demanding or dangerous tasks taken over by robotic counterparts.

Carnegie Mellon University
Artur Dubrawski, director of the Auton Lab and senior faculty in the Robotics Institute at Carnegie Mellon University

Artur Dubrawski, director of the Auton Lab and senior faculty in the Robotics Institute at Carnegie Mellon University, used to be the CTO at Aethon, a Pittsburgh-based robotics company. Aethon makes the Tug robot, which is often used to make deliveries in hospitals, pulling carts carrying everything from linens to medicines and food.

Through the deployments he worked on while at Aethon, he did not see robots replacing human workers, but helping them.

“There’s concern about robotics eliminating jobs, but in my practice that wasn’t the case,” Dubrawski said. “In the hospitals I watched through our deployments, nobody who worked in delivery lost their jobs. The efficiency increased. The quality of those employees’ lives picked up.”

At one hospital that was using a Tug robot, an employee told Dubrawski that his knees had always hurt him when he was pushing the cart to make deliveries. With the robot, however, he began focusing on making sure the carts had the right supplies and then pushing a button on a touch-screen to have the robot take it to make the delivery.

The worker’s knees didn’t hurt anymore.

Think about human/robot interactions

While working with a robot helped that hospital employee, other people may be anxious about working with a robot — particularly an autonomous one. The image that often comes to mind: Out-of-control, malevolent robots like the ones on Battlestar Galactica or The Terminator.

Add to that the fear of a robot accidentally hurting someone or taking their job, and employee concerns about their new, non-human co-workers could quickly arise.

It’s going to be up to the company, and likely the IT department, to work with employees, train them and put them at ease with robots.

“Having people who are willing to work with the robots is important,” said Gennert. “The fact that so many young employees today are already digital natives and feel very comfortable with computers means those folks will be pretty eager adopters of technology. And if people see how it helps them in their jobs, they’ll be more happy to have the robots come along.”

Olds noted that part of the job for IT — and anyone introducing robots into the enterprise — will be to make it clear to employees what’s happening. Are the robots replacing workers? Are the robots aimed at making some jobs easier?

“It’s important that employees get comfortable with the new tools and management needs to foster that sort of cooperation,” said Olds. “There will certainly be some people displaced by robots, which will cause them to resent them. But this won’t be the majority of workers. The majority of workers will carry on as before, but will probably find their jobs become more interesting and less wearing on them with the addition of their robot helpmates.”

Think infrastructure

IT managers will need to assess their infrastructure to figure out what they need to not only run robots but to have them safely and efficiently connect with other aspects of the corporate network, take orders from people in different departments, have them download information, track them throughout the property and even help robots deal with things like automatic doors and elevators.

“We are still in the early stage of utilizing robotics and A.I. in enterprise IT,” said Andy Chang, a spokesman for KUKA, a German-based robot manufacturer. “It is extremely important to make sure that you have a good infrastructure foundation to scale for the next 10 years.”

According to Chang, companies tend to utilize proprietary communication protocols, which can make extracting machine information difficult. “Existing networks can scale in the short term, but be ready to invest in new technologies such as 5G or Li-Fi as they become commercially available,” he added. “It will be critically important.”

Dubrawski added that it’s also a matter of thinking about how robots will need to communicate with the physical world, as well as with other company computers.

“As an IT manager, you need to have the robot access the networking system in your [company]…and communicate with each other and be able to convey their whereabouts to whoever sends them on a delivery trip, as well as to those who are waiting for them. We want to know where they are and if they get into trouble, and how to deal with them remotely if they get stuck. You need to be able to resolve navigational challenges, or if it might be cornered by a bunch of kids.”

Source: Computerworld-With robots on the job, it won’t be IT as usual

Why automation doubles IT outsourcing cost savings

New research analyzes automation’s impact on the IT outsourcing market, revealing double-digit productivity improvements and specific cost reductions between 14 percent and 28 percent.

Outsourcing consultancy and research firm Information Services Group (ISG) this week unveiled a new research report to quantify the cost savings and productivity gains from automating IT services.

The inaugural Automation Index shows improvements in productivity fueled by automation can more than double the cost savings typically derived from outsourcing IT. Total cost reduction ranged from 26 percent to 66 percent, depending on the service tower, with 14 to 28 percentage points of these savings directly attributable to automation, according to ISG. (The typical cost savings from labor arbitrage and process improvements alone range from 20 percent to 30 percent).

The report is based on cost and labor data from ISG’s database covering outsourcing agreements with an annual contract value of $10 million or more in which service automation is a core component. The index is one of the first to quantify the impact of automation on IT services. Automation-related technologies and platforms improve the productivity of employees by enabling them to do more with less and prevent problems before they arise, translating into lower costs for buyers by not only reducing the number of provider employees needed to perform the work but also by reducing the amount of work that needs to be performed.

The result, says Steve Hall, partner with ISG Digital Services, is a buyer’s market that’s putting tremendous pressure on services providers to deliver more and more savings to stay competitive. “As automation moves up the IT process value chain and into business processes, it will eliminate a significant amount of work through problem avoidance and self-healing, and with it, a significant amount of the headcount needed to deliver large-scale ITO services,” Hall said in a statement accompanying the report.

Where automation has the biggest impact

Automation is having the biggest impact on areas in which employees manage physical devices, such as network services. Most IT towers see an average 25 percent decrease in the number of resources required as a result of automation, but certain IT services experience a 50 percent headcount reduction, according to ISG. ISG found that network and voice costs are declining by 66 percent mostly due to the convergence of voice, video and data solutions built on highly standardized and virtualized capabilities, an environment ripe for leveraging automation. Service desk and end user support costs declined by 26 percent due to increased adoption of self help and remote support, the introduction of self-healing functionality, and significant automation of level one and two incidents.

Higher-order automation

Most of today’s automation is focused on computerizing repetitive tasks based on standard operating procedures but more complex automation is beginning to emerge that takes advantage of more advanced data mining and machine learning capabilities, says Stanton Jones, ISG director of research. That higher-order automation can make operational decisions with no human involvement.

In order to seize the benefits of increased automation and plummeting IT services costs, however, buyers will have to transform to more standardized technology stacks across the IT organization. “The more clients standardize things like operating system instances, application interfaces, ITIL processes, and network infrastructure, the easier it is to automate operations,” says Jones. “Standardization means less interfaces, less complexity and fewer decisions that need to be made, therefore, it becomes easier to automate.”

Buyers should also approach process automation tools with standardization in mind. “Service providers are driving increased productivity into their services by using data mining and machine learning to aggregate and correlate data and then improve the quality and timeliness of decision making for routine and repetitive tasks,” Jones says. “Clients can enable and execute these transformations by accepting standard processes and technologies providers bring to the table.”

Source: companies need to know when considering automation

How To Make BPMS And RPA Work Together

Robotic Process Automation (RPA) has been gaining traction in recent years. It has moved from being a mere buzzword to being a priority on organization’s to-do list.

Being a Business Process Management (BPM) practitioner, I am interested in exploring how a BPM software (BPMS) can work with an RPA tool. If you look at the leading BPMS vendors from different magic quadrants, you will see a trend developing. Pegasystems a BPMS vendor acquired an RPA tool last year. Appian, another BPMS/low-code vendor had RPA front and center at their annual conference.

In my opinion, RPA compliments BPMS very nicely, it can actually increase adoption of BPMS, and vice versa. In rest of this article, I am going to explore two different approaches that can be used to make a BPMS and an RPA tool work together in harmony.

Process-Driven RPA

A process cannot exist in a silo, it has to integrate with other systems in order to deliver real benefits. Unfortunately, in most organizations, a fully integrated process is only part of the vision and not reality.

Unfortunately, in most organizations, a fully integrated process is only part of the vision and not reality.

Various factors such as mergers, acquisitions, legacy software or resource constraints can stop you from building those much-needed integrations. Lack of integrations definitely has a negative impact on adoption and usability of the automated process.


Consider a basic version of the order management process. You have automated the process using a BPMS, but it lacks integration with let’s say the shipping vendor’s system.

In order to complete the Ship Order activity shown in the process above, you will need to work on multiple systems. Here is a quick list of different tasks that you might need to perform.

  • Login to order management system
  • Search and open order details
  • Login to the shipping vendor’s system
  • Copy and paste all the required data from order management system to shipping system
  • Ship the order and copy tracking number from shipping system back into order management system
  • Log out and close the shipping system
  • Mark order as shipped in order management system
  • Log out and close the order management system

If you get one or two orders a day, these tasks might not be a big deal, but if this is happening 100 times a day, then you are spending a considerable amount of time on non-value add work.


If you have similar situations in your organization, where processes have been automated using a BPMS but due to lack of integrations have resulted in swivel chair activities, then RPA tools can help you.

A swivel chair activity means that a user has to perform tasks in multiple systems in order to complete a single activity of a process. In the order management process example, Ship Order was a swivel chair activity.

The idea behind Process-Diven RPA approach is that your process keeps running inside a BPMS without any major modifications. You automate non-value add swivel chair activities by using the digital workforce (bots) provided by the RPA tool. Referring to the earlier example of order management process, once your process reaches the Ship Order activity, instead of a human doing all the tasks, a trained bot can perform all the tasks.

This approach can help you (in a way) integrate with systems that might not have been possible otherwise and more importantly free up your human resources, who can work on value-add work instead.

RPA-Initiated Process

A bot is great when you have well-defined repeatable tasks that it can perform, but what happens when there are data anomalies or errors? It is simply not feasible to train a bot with all possible exception cases (unless it is a self-learning bot, topic for another day).


To further elaborate this approach, let’s take a look at trade reconciliation process. This process usually happens at end of a trading day, and the goal is to make sure that balance is accurate in two or more systems.

The figure above shows two hypothetical systems used for trading. Here is a quick list of different tasks that an agent might need to perform for reconciliation.

  • Login to trade management system of the firm
  • Search and open the customer in trade management system
  • Login to broker system
  • Search and open the customer in broker system
  • Verify that end of day balance in both systems is same
  • Log out and close the trade management system
  • Log out and close broker system

Now consider the exception case where at end of the day, the balance was not same in both systems. In this exception case, an agent will need to perform follow-up tasks, which might require a call or email to the client and broker to find out the reason balance is not same.


In such scenarios, a bot can be trained to perform the daily repeatable tasks of checking balance in both systems, but training it on all exception scenarios, follow-ups, and follow-up actions might not be possible, and this is where BPMS comes to the rescue.

As the name suggests, the idea behind RPA-Initiated Process approach is that when a bot has not been trained to handle exception cases, it requests human intervention. The bot completes its processing, kicks off a human activity inside BPMS and moves on to the next set of work. This approach works great when a majority of the time a bot is able to complete processing without issues, but in those minor instances when they do find anomalies, a process is kicked off in BPMS so that a human can follow-up and resolve the issue.

This approach works great when a majority of the time a bot is able to complete processing without issues, but in those minor instances when they do find anomalies, a process is kicked off in BPMS so that a human can follow-up and resolve the issue. This again lets your resources focus on actual value-add work instead of spending time on mundane tasks.


In my opinion, BPMS and RPA are a great match. The two approaches discussed in this article show that if both technologies are used in harmony they can really complement each other and increase adoption.

Share your thoughts on how you are planning to use BPMS and RPA in your organization. What opportunities or challenges do you see in implementing both together?

Source: To Make BPMS and RPA Work Together 

What companies need to know when considering automation

As the hype continues around Robotic Process Automation (RPA) and Artificial Intelligence (AI), organizations are looking to invest additional efforts to better understand potential benefits and risks associated with these.

The fact of the matter: RPA and AI are already a reality and many service providers are taking an active role in the lookout for opportunities to maximize their service delivery models, profits and increased client satisfaction.

Below are some ideas and considerations for organizations prior to determine a course of action:

  • Understand the benefits beyond the hype: Organizations should have a realistic perspective on the potential benefits RPA/AI can bring to their environment. Obviously the excitement to bring those to life and all the value add innovation that can be achieved are phenomenal. Prior to executing, just make sure investments are made towards a sound business case – in which a realistic perspective of benefits and risks is presented, not the hype effect.
  • Determine demarcation points in order to maximize benefits: If service providers are already deploying RPA and AI to some of the services offered to an organization, there is a good leverage case to be used. These should translate in both financial/non-financial benefits to the services provided. In order to achieve this, it is important to determine what the opportunities are and activities that can be automated through the service provider’s capabilities. By doing so, organizations can potentially minimize capital investments, and at the same time allow RPA and AI related risks to be managed by such service providers.
  • Review your service provider’s agreements prior to adopting RPA and AI: Like other disruptors such as Cyber and Cloud, it is important for organizations to have appropriate commercial terms in place prior to entertain RPA/AI services so that the organization’s interests and risks are aligned with the organization’s procurement, outsourcing, privacy and supplier risk policies. The hype effect shall not create unnecessary exposure or challenges for the organizations that otherwise could have been prevented. 
  • Determine overlap between initiatives across the organization: It is common for different areas within an organization to work independently on their respective challenges and opportunities. In order to determine the organizations best course of action, a holistic approach aligned with the organization’s strategy should exist. This will enable the organization to identify overlaps and also promote collaboration within the organization. Another important point goes back to basic strategic sourcing principles around effective governance and economies of scale – as financial benefits and costs should be clearly stated and understood.
  • The importance of Governance and Risk Management should not be understated: I know I have written this topic before but I felt the need to reemphasize the importance to having “all ducks in place”. This is particularly important for organizations in highly regulated sectors (e.g., Financial Services, Insurance and Healthcare), for which this should be considered a top priority.        Remember that organizations should not compromise their ability to comply with their respective regulatory requirements, as this can have a significant impact to the organization’s reputation and bottom line.
  • Enjoy the excitement and discovery process but do not underestimate change management: There are a lot of “pluses” bringing disruptive technologies to an organization. Take the time to enjoy and generate the required momentum – so that change management activities are positively perceived across the different organization levels and generations. Usually organizations that pursue these through business transformation exercises tend to dig deeper on the potential additional values the organization can achieve beyond the hype. For example, the need to change processes that, although efficient, will require significant changes to support the organization’s desired future state RPA and AI. That also help the organization’s internal staff to gain valuable knowledge and experience through hands on experiences as the business transformation is being executed. In other words, the excitement and hype may help foster employee’s engagement.
  • Understand where the market is going beyond the hype: There are talks of RPA/AI organizations going public or being a target to large service providers such as IBM and CapGemini. Before entertaining a direct relationship with a specific RPA/AI service provider, it is very important to understand the potential issues of a fourth party and the implications to the organization service delivery model. For example, the Bank of New York Mellon faced significant challenges due to an acquisition of one of its main service providers by another institution back in August 2015 – The Wall St. Journal has an interesting article on it.

The conclusion: Go ahead and have fun! At the same time, do not lose sight of potential exposures for the organization. In today’s world, organizations cannot afford reputational risks / impacts to their brand and clients. Remember that the higher the benefits, the higher the risks. At the same time, organizations cannot afford to stay put, as our worlds breathes change.

A final and important update: the Wall Street Technology Conference is taking place in New York City on May 24. Further details can be found here. I look forward to seeing you there!!!

About This Year’s Wall St Technology Conference: Managing Risk & Reward in a Digital World

2016 will be the year that companies go beyond the hype, get to reality and actually invest in digital innovations that produce results and deliver ROI. It is the year that providers will go from selling buzz-ware to offering real industry-driven solutions.

Digital value chains will become a reality and organizations will reap the true power of data and insights. But along with new opportunities, there are increased risk of cyber-security hacks, data privacy breaches and regulatory issues. Financial services and insurance companies have to balance their strategic priorities with the risks, regulatory and cost objectives. The advent of Digital banking and mobile payment systems coupled with consumerization of IT, automation and real-time analytics is changing how CXOs procure and implement new solutions.


Source: companies need to know when considering automation

Robotic process automation is killer app for cognitive computing

Robotic Process Automation (RPA) is an increasingly hot topic in the digital enterprise. Implementing software robots to perform routine business processes and eliminate inefficiencies is an attractive proposition for IT and business leaders. And providers of traditional IT and business process outsourcing facing potential loss of business to bots are themselves investing in these automation capabilities as well.

While the basic benefits of RPA are relatively straightforward, however, these emerging business process automation tools could also serve as en entry point for incorporating cognitive computing capabilities into the enterprise, says David Schatzky managing director with Deloitte.

By injecting RPA with cognitive computing power, companies can supercharge their automation efforts, says Schatzky, who analyzes the implications of emerging technology and other business trends. By combining RPA with cognitive technologies such as machine learning, speech recognition, and natural language processing, companies can automate higher-order tasks that in the past required the perceptual and judgment capabilities of humans.

Some leading RPA vendors are already combining forces with cognitive computing vendors. Blue Prism, for example, is working with IBM’s Watson team to bring cognitive capabilities to clients. And a recent Forrester report on RPA best practices advised companies to design their software robot systems to integrate with cognitive platforms. talked to Schatzky about RPA adoption rates, the budding relationship between software robots and cognitive systems, the likelihood that the combination of the two will replace traditional outsourcing, and the three steps companies should take before implementing RPA on a wider scale. Where are most companies in terms of their adoption of RPA?

David Schatzky, managing director, Deloitte: RPA is a new topic to some and a well understood one to others. More and more IT leaders have heard of the term and at least know what it is in principle. Adoption thus far is pretty modest. RPA has been more widely adopted in Europe and Asia than it has been in the U.S. And even those companies in the U.S. that have adopted RPA are typically just piloting it. Why did RPA catch on more rapidly in Asia and Europe?

Schatzky:That’s due to the level of business process outsourcing that has taken place there. Asia is the hope of business process outsourcing and European companies have been eager to cut the costs of onshore operation using RPA. Also, one of the leading RPA companies, Blue Prism, is based in Europe. Why are you focusing on the potential combination of RPA and cognitive computing systems in particular?

Schatzky: I think it will help to broaden the application of RPA and increase the value it delivers to the companies that adopt it. Cognitive technology is progressing rapidly, but many companies don’t have a clear path to taking advantage of these technologies. They’re not sure how and where to put them to use.

RPA is a platform that can provide clear use cases for applying cognitive capabilities. Companies can install it to automate processes and it provides a framework or platform to integrate with cognitive systems to take automation to the next level. It’s almost the ‘killer app’ for cognitive computing.

RPA is very useful technology, but it’s not terribly intelligent technology. It only performs tasks with clear-cut rules. You can’t substitute RPA for human judgment. It can’t perform rudimentary tasks that require perceptual skills, like locating a price or purchase order number in a document. It can identify a happy customer versus an unhappy customer. Cognitive takes the sphere of automation that RPA can handle and broadens it. Where will be the most beneficial use cases for using RPA in conjunction with cognitive technology?

Schatzky: A lot of them are in the front office: classifying customer issues and routing them to the right person, deciding what issues need to be escalated, extracting information from written communication. Who tends to lead these RPA efforts—an IT leader or a business process owner?

Schatzky: It’s mixed. Sometimes it’s led by the process owner in the business. They learn about RPA and identify an opportunity to deploy it and improve efficiency. In other cases, IT has been leading the effort. It’s indicative of the broader trend of tech-centric decision being made increasingly in the business and not just IT.

Source: – Robotic process automation is killer app for cognitive computing

Making the Case for Employing Software Robots

One of the main tenets of advancing technology is to free up the time and effort workers are often required to put into relatively mundane tasks. Automating processes that once took hours for a person to complete has been a boon to a business’ bottom line while allowing IT workers to focus on tasks more central to advancing a company’s strategic initiatives. When it comes to Robotic Process Automation (RPA), Rod Dunlap, a director at Alsbridge, a global sourcing advisory and consulting firm, understands how RPA tools can positively impact workflow in industries such as health care and insurance. In this interview with CIO Insight, Dunlap expands on the RPA ecosystem, when it makes sense to employ RPA tools—and when it doesn’t.

For those unfamiliar, please describe Robotic Process Automation and explain a basic example of it in use.

RPA tools are software “robots” that use business rules logic to execute specifically defined and repeatable functions and work processes in the same way that person would. These include applying various criteria to determine whether, for example, a healthcare claim should be accepted or rejected, whether an invoice should be paid or whether a loan application should be approved.

What makes RPA attractive to businesses?

For one thing RPA tools are low in cost – a robot that takes on the mundane work of a human healthcare claims administrator, for example, costs between $5K and $15K a year to implement and administer. Another advantage is ease of implementation. Unlike traditional automation tools, RPA systems don’t require extensive coding or programming. In fact, it’s more accurate to say that the tools are “taught” rather than “programmed.” Relatedly, the tools can be quickly and easily adapted to new conditions and requirements. This is critical in, for example, the healthcare space, where insurance regulations are constantly changing. And while the tools require some level of IT support, they don’t have a significant impact on IT infrastructure or resources or require changes to any of the client’s existing applications.

What are the drawbacks of RPA?

RPA tools are limited in terms of their learning capabilities. They can do only what they have been taught to do, and can’t reason or draw conclusions based on what they encounter. RPA tools typically cannot read paper documents, free form text or make phone calls. The data for the Robots must be structured.

In what industries does RPA make the most sense?

They make sense in any situation that has a high volume of repeatable or predictable outcomes, on other words, where the same task is repeated over and over. We’ve seen a lot of adoption in the Insurance, Financial, Healthcare, Media, Services and Distribution industries.

Where does it make the least sense?

They don’t make sense in situations that have a high volume of one-off or unusual situations. To take the healthcare claims processing example, RPA is ideal for processing up to 90 percent of claims that an insurer receives. The remaining 10 percent of claims are for unusual situations. In these cases, while you could teach the robots the rules to process these claims, it’s more cost-effective to have a human administrator do the review.

If you automate a process once done by humans, and have it perfected by a robot, is it possible for the robot to determine a better way to accomplish the task?

Not with RPA. As mentioned, these tools will execute tasks only in the way in which they were taught. They can’t observe and suggest a different way to do things based on their experience, but what you are suggesting is indeed where the industry is heading.

What sort of data can be learned from RPA?

RPA tools can’t really provide insight from data on their own. They can log detailed data about every transaction they process. This can then be fed into a number of tools that will provide operation statistics. Also, they can work in tandem with more sophisticated cognitive tools that use pattern recognition capabilities to process unstructured data. For example, insurance companies have huge volumes of data sitting on legacy systems in a wide range of formats. Insurers are looking at ways to apply the cognitive tools to process and categorize this data and then use RPA tools to feed the data into new systems. Retailers are looking to apply the tools in similar ways to gain insight from customer data.

How much human oversight is needed to ensure mistakes are avoided?

The robots won’t make “mistakes” per se, but oversight is necessary to make sure that the robots are updated to reflect changes in business conditions and rules. An operator, similar to a human supervisor, can start and stop robots, change the tasks they perform and increase throughput all without worrying about who gets the window office.

Source: the Case for Employing Software Robots

4 Things Robots Need to Learn Before Working With Humans

The robots are coming. And really, in some ways, they’re already here. If you’ve ever tripped over a robot vacuum, you’ve actually waded into the fascinating frontier that is human-robot interaction. If humans are at all going to get along with increasingly sophisticated robots, we need to figure out how we’re going to interact with them, and in turn they’ll need to adapt to us.

This technological revolution is different than those that came before it. In the Industrial Revolution, the static, hulking machines required humans to fundamentally change the way they worked. But in the robot revolution, both parties have to make compromises. You’ll have to learn to communicate with a new kind of being, and that new kind of being will have to help you along as well. Subtle communications, like a robot pretending to struggle with a heavy object it’s handing to you so you’re not surprised by the weight, will be pivotal for our two species to work together without driving each other crazy.

Luckily, ace roboticists like UC Berkeley’s Anca Dragan are diving deep into the fascinating problems of human-robot interaction before they become problems. Check out the video above to see Dragan’s top four challenges with the coming robo-revolution.

Source: Wired-4 Things Robots Need to Learn Before Working With Humans

The 3 Ways Work Can Be Automated

We are at an interesting tipping point regarding how and where work gets done. As business leaders and managers, we have become increasingly capable of engaging a workforce that is some combination of virtual and on site, part time and full time, permanent and contingent. But just when we’ve sorted out preferred management routines, there is an entirely new landscape emerging with technology options central to the work and possibly your business model: work automation. How, when, and where should leaders be thinking about applying the various automation technologies to their businesses?

There are currently three technological enablers of work automation: robotic process automation, cognitive automation, and social robotics. Each technology fits a different kind of work and has different implications depending on the work to be done, as described in the chart below.

The simplest and most mature so far is robotic process automation. It can be used to automate high-volume, low-complexity, and routine tasks. It is particularly effective in automating the so-called “swivel chair” tasks, where data needs to be transferred from one software system to another. These tasks are traditionally done by humans. For example, they may involve taking inputs from emails or spreadsheets, processing the information by applying certain rules, and then entering the output into some other business systems, such as an ERP or a CRM. Creating a virtual workforce of software robots can help companies streamline operational processes as well as increase the quality and cost-effectiveness of shared services.

Nevertheless, most of the current excitement around work automation stems from systems that can replace humans in nonroutine, complex, creative, and often exploratory tasks — in other words, systems that can automate human cognition, or cognitive automation. Developments in machine learning, powered by scalable computing resources in the cloud and heavy investment in exceptional human talent by the large players in the IT industry, are making computers capable of recognizing patterns and understanding meaning in big data in a cunningly human-like way. This “recognition intelligence” is showcased in systems for voice recognition, voice-to-text, natural language understanding, image understanding, and a host of other applications that are increasingly becoming available to consumers and companies.

Companies can use these cognitive automation technologies in three ways. First, they can further automate, or completely reengineer, their business processes. Take, for example, the car insurance industry. Instead of having human agents visit cars to assess the damage, an app used by the car policy owner and powered with image recognition intelligence could process photos of the car damage, assess the degree of the damage, estimate and classify the size of the claim, and pass the information for final approval to a human, thereby significantly simplifying the claims process in terms of both time and cost. Cognitive automation like Google Glass can transform the work of a flight attendant, for example. The ability of such technology to enable traditional jobs to be disaggregated and to supplement or replace routine activities presents opportunities in efficiency, effectiveness, and impact.

The second area of opportunity with cognitive automation is for companies to develop new products and services. In the previous example, the intelligent app could be part of a new offering to car insurance clients, perhaps with added features such as a chatbot that could provide additional, on-demand advice about insurance to the policy owner.

Finally, cognitive automation can be used to gain new insights into big data. When it comes to transforming a company’s strategy around the future of work, talent analytics combined with machine learning can be a very powerful tool for analysis and prediction.

Another area that is rapidly evolving is social robotics. Unlike their predecessors, this new generation of robots is not bolted on an assembly line; they are mobile and move around in our everyday world. They can be drones that fly or swim, anthropoid robots that walk, or swarm robots that roll on wheels. They are programmable and can adapt to new tasks. This new generation of social robotics can automate routine as well as nonroutine tasks. Freed from the assembly line, the social robots can collaborate with humans in a variety of applications that were unthinkable a few years ago.

A good example is the Kiva robots that Amazon has been using to increase the efficiency of its order fulfillment process. Instead of walking the aisles to find the right packages, humans now stand on platforms while an army of social robots brings the right package to them at the right time. By reengineering the process using robots, Amazon did not replace the human workers but rather made them more productive in the same way the aforementioned app allows human adjustors to take on more cases by focusing on the “higher value added” activities while the app takes on the more routine aspects of the job.

Amazon’s employees now take 15 minutes to fulfill some orders instead of 90 minutes, an increase of 20% in efficiency; the small size of the robots also allowed Amazon to increase the size of ist inventory by 50%. Management oversees the entire fulfillment process, including the work interactions between robots and humans.

As the half-life of skills continues to shrink, the growing premium on reskilling is causing many organizations to rethink the risks associated with full-time employment in order to reduce the risk of obsolescence. The different variations of work-task automation, like the ones here, can deliver viable solutions to all of the above concerns. Selecting the right technology for automating work tasks and improving performance is therefore critical for business, as is the alignment of the selected technology with a comprehensive strategy for the future of work.

Source: Harvard Business Review-The 3 Ways Work Can Be Automated